Digital images are being used in numerous applications, for example, with acquisition devices like still and/or video cameras. Moreover, digital-image sensors are also used with mobile-phone devices and/or so-called smart phones in a widespread manner.
It is well known that any of these digital-image acquisition devices will, due to the characteristics of digital-image sensors used, intrinsically introduce digital-image defects into the acquired digital images. These image defects are easily detectable by the human visual system as they are out of context and can be of very bright or very dark appearance. However, they may also be masked by a texture of the digital image such that the defect may not be visible.
In other words, image sensors are well known to be imperfect devices. Thus, faulty elements of an image sensor can show up in the light-sensitive array. Image defects caused by these faulty elements can appear as isolated, faulty pixels (so-called “singlets”) or adjacent faulty pixels (so-called “couplets”). Although these image defects may be easily detectable by the human eye, their filtering and cancellation is a complex task to be executed by the image-acquisition device. In that regard, defect cancellation is of primary importance.
In addition, not all image defects are “static”, i.e., of a stable appearance, independent from other factors. In contrast, some of the digital-image effects are always visible, whereas others may show up only in low-light conditions, depending, for example, on the image-acquisition settings such as integration time, analog gain, digital gain, etc.
Various filtering techniques have been developed in order to reduce and/or eliminate such image defects. However, many of these techniques are associated with numerous drawbacks and problems that are bound up with, for example, inadequate performance, processing complexity, and processing costs that make it difficult to employ these techniques in portable image-acquisition devices. Moreover, these solutions generally change their defect-correction characteristics depending on various external factors, for example, acquisition settings in terms of integration time, analog gain, digital gain, and the like. However, in order to achieve satisfying defect-correction performance for different variations of these factors, cumbersome tuning and calibration efforts have to be performed.